DIFFRAC: a discriminative and flexible framework for clustering
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[1] Alan M. Frieze,et al. Improved Approximation Algorithms for MAX k-CUT and MAX BISECTION , 1995, IPCO.
[2] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[3] Chris H. Q. Ding,et al. Spectral Relaxation for K-means Clustering , 2001, NIPS.
[4] Adrian S. Lewis,et al. Twice Differentiable Spectral Functions , 2001, SIAM J. Matrix Anal. Appl..
[5] Claire Cardie,et al. Proceedings of the Eighteenth International Conference on Machine Learning, 2001, p. 577–584. Constrained K-means Clustering with Background Knowledge , 2022 .
[6] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[7] Michael I. Jordan,et al. On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.
[8] Tomer Hertz,et al. Learning Distance Functions using Equivalence Relations , 2003, ICML.
[9] Jean Charles Gilbert,et al. Numerical Optimization: Theoretical and Practical Aspects , 2003 .
[10] Michael I. Jordan,et al. Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.
[11] Dale Schuurmans,et al. Maximum Margin Clustering , 2004, NIPS.
[12] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2004 .
[13] Chaitanya Swamy,et al. Correlation Clustering: maximizing agreements via semidefinite programming , 2004, SODA '04.
[14] Christoph Schnörr,et al. Semidefinite Clustering for Image Segmentation with A-priori Knowledge , 2005, DAGM-Symposium.
[15] Alexander Zien,et al. Semi-Supervised Classification by Low Density Separation , 2005, AISTATS.
[16] Dale Schuurmans,et al. Unsupervised and Semi-Supervised Multi-Class Support Vector Machines , 2005, AAAI.
[17] Michael I. Jordan,et al. Learning Spectral Clustering, With Application To Speech Separation , 2006, J. Mach. Learn. Res..
[18] Nello Cristianini,et al. Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem , 2006, J. Mach. Learn. Res..
[19] Gregory Shakhnarovich,et al. An investigation of computational and informational limits in Gaussian mixture clustering , 2006, ICML '06.
[20] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[21] J. Frédéric Bonnans,et al. Numerical Optimization: Theoretical and Practical Aspects (Universitext) , 2006 .
[22] Rong Jin,et al. Generalized Maximum Margin Clustering and Unsupervised Kernel Learning , 2006, NIPS.
[23] Ivor W. Tsang,et al. Maximum Margin Clustering Made Practical , 2009, IEEE Trans. Neural Networks.